Skip to main content

Energy Expenditure Analysis: A Comparative Research of Based on Mobile Accelerometers

  • Conference paper
Ambient Assisted Living and Daily Activities (IWAAL 2014)

Abstract

Nowadays, the Metabolic Equivalent Task (MET) is the most often used indicator for energy expenditure (EE) calculation of physical activity (PA). The use of novel devices based on inertial movements (e.g. accelerometers) enable the measurement of the PA using “counts”:, where each count is an aggregated value that can be used to determine the number of METs. For some kind of users, such as elderly people or patients in AAL environments, the MET is an important indicator in order to maintain a good health. At present, there exist several types of inertial devices that enable different forms of count calculation and types of exercise monitoring. From the point of view of process analysis and infrastructure needed, they differ in several aspects, such as extra devices required and out-of-device processing. This paper presents a survey analysis about the possibilities of different types of accelerometers to measure EE in AAL contexts. To achieve this objective, we have conducted several experiments based on the performing of different exercises with different accelerometers placed in different body parts.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. World Health Organization. Milestones in health promotion: Statements from Global Conferences (2009)

    Google Scholar 

  2. U.S. Department of Health and Human Services. Physical Activity and Health: A Report of the Surgeon General. Atlanta, GA: U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion (1996)

    Google Scholar 

  3. Sallis, J.F., Saelens, B.E.: Assessment of physical activity by self-report: status, limitations, and future directions. Research quarterly for exercise and sport 71(2 Suppl), S1–S14 (2000)

    Google Scholar 

  4. Goran, M.I., Poehlman, E.T.: Total energy expenditure and energy requirements in healthy elderly persons. Metabolism 41(7), 744–753 (1992)

    Article  Google Scholar 

  5. Ainsworth, B.E., et al.: Compendium of physical activities: an update of activity codes and MET intensities. Medicine and Science in Sports and Exercise 32(9, Supp/1), S498–S504 (2000)

    Google Scholar 

  6. Byrne, N.M., et al.: Metabolic equivalent: one size does not fit all. Journal of Applied Physiology 99(3), 1112–1119 (2005)

    Article  Google Scholar 

  7. Freedson, P.S., et al.: Evaluation of artificial neural network algorithms for predicting METs and activity type from accelerometer data: validation on an independent sample. Journal of Applied Physiology 111(6), 1804–1812 (2011)

    Article  Google Scholar 

  8. Yang, C.-C., Hsu, Y.-L.: A review of accelerometry-based wearable motion detectors for physical activity monitoring. Sensors 10(8), 7772–7788 (2010)

    Article  Google Scholar 

  9. Chen, K.Y., Bassett, D.R.: The technology of accelerometry-based activity monitors: current and future. Medicine and Science in Sports and Exercise 37(11), S490 (2005)

    Google Scholar 

  10. Calloway, D.H.: Zanni, Eleni. Energy requirements and energy expenditure of elderly men. The American Journal of Clinical Nutrition 33(10), 2088–2092 (1980)

    Google Scholar 

  11. Pinheiro Volp, A.C., et al.: Energy expenditure: components and evaluation methods. Nutr. Hosp. 26(3), 430–440 (2011)

    Google Scholar 

  12. Garatachea, N., Torres Luque, G., Gonzalez Gallego, J.: Physical activity and energy expenditure measurements using accelerometers in older adults. Nutr. Hosp. 25(2), 224–230 (2010)

    Google Scholar 

  13. Bourke, A.K., et al.: Embedded fall and activity monitoring for a wearable ambient assisted living solution for older adults. In: Engineering in Medicine and Biology Society (EMBC), 2012 Annual International Conference of the IEEE, pp. 248–251. IEEE (2012)

    Google Scholar 

  14. Goran, M.I., Poehlman, E.T.: Endurance training does not enhance total energy expenditure in healthy elderly persons. American Journal of Physiology 263, E950-E950 (1992)

    Google Scholar 

  15. Clegg, A., et al.: Frailty in elderly people. The Lancet 381(9868), 752–762 (2013)

    Article  Google Scholar 

  16. Tallarida, R.J., Murray, R.B.: Area under a Curve: Trapezoidal and Simpson’s Rules. In: Manual of Pharmacologic Calculations, pp. 77–81. Springer, New York (1987)

    Chapter  Google Scholar 

  17. Santos-Lozano, A., et al.: Actigraph GT3X: Validation and Determination of Physical Activity Intensity Cut Points. International Journal of Sports Medicine 34(11), 975–982 (2013)

    Article  Google Scholar 

  18. Ainsworth, B.E., et al.: Compendium of physical activities: an update of activity codes and MET intensities. Medicine and Science in Sports and Exercise 32(9 Supp/1), S498–S504 (2000)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this paper

Cite this paper

Ruiz-Zafra, Á., Gonzalez, E.O., Noguera, M., Benghazi, K., Heredia Jiménez, J.M. (2014). Energy Expenditure Analysis: A Comparative Research of Based on Mobile Accelerometers. In: Pecchia, L., Chen, L.L., Nugent, C., Bravo, J. (eds) Ambient Assisted Living and Daily Activities. IWAAL 2014. Lecture Notes in Computer Science, vol 8868. Springer, Cham. https://doi.org/10.1007/978-3-319-13105-4_7

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-13105-4_7

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-13104-7

  • Online ISBN: 978-3-319-13105-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics